Along with the widespread use of the Internet, information resources on the Internet have been expanding exponentially, causing problems of “information overload” and “information disorientation”. A user may often be lost in a space of tremendous information, and cannot smoothly find required information. Therefore, Internet-oriented technologies such as information search, information filtering and collaborative filtering have emerged. One example is e-commerce recommendation systems. These e-commerce recommendation systems directly interact with a user, simulate a salesperson of a shop to provide merchandise recommendation to the user, and help the user to find needed merchandise and complete the purchase process. The existing recommendation systems are developed using real-life examples, e.g., product recommendation through another product, information recommendation through other information, and group recommendation through another group. These recommendation systems, however, do not have wide enough coverage, or high enough accuracy. Under an ever-intensifying competition environment, existing recommendation systems may incur a loss of customers because of these problems, negatively impacting sales volume and browsing volume of a website.